Myocardial infarction and stroke subsequent to urinary tract infection (MISSOURI): protocol for a self-controlled case series using linked electronic health records

Introduction There is increasing interest in the relationship between acute infections and acute cardiovascular events. Most previous research has focused on understanding whether the risk of acute cardiovascular events increases following a respiratory tract infection. The relationship between urinary tract infections (UTIs) and acute cardiovascular events is less well studied. Therefore, the aim of this study is to determine whether there is a causal relationship between UTI and acute myocardial infarction (MI) or stroke. Methods and analysis We will undertake a self-controlled case series study using linked anonymised general practice, hospital admission and microbiology data held within the Secure Anonymised Information Linkage (SAIL) Databank. Self-controlled case series is a relatively novel study design where individuals act as their own controls, thereby inherently controlling for time-invariant confounders. Only individuals who experience an exposure and outcome of interest are included. We will identify individuals in the SAIL Databank who have a hospital admission record for acute MI or stroke during the study period of 2010–2020. Individuals will need to be aged 30–100 during the study period and be Welsh residents for inclusion. UTI will be identified using general practice, microbiology and hospital admissions data. We will calculate the incidence of MI and stroke in predefined risk periods following an UTI and in ‘baseline’ periods (without UTI exposure) and use conditional Poisson regression models to derive incidence rate ratios. Ethics and dissemination Data access, research permissions and approvals have been obtained from the SAIL independent Information Governance Review Panel, project number 0972. Findings will be disseminated through conferences, blogs, social media threads and peer-reviewed journals. Results will be of interest internationally to primary and secondary care clinicians who manage UTIs and may inform future clinical trials of preventative therapy.


GENERAL COMMENTS
The study protocol is sound and I have no additional comments.

REVIEWER
Lee, Joseph University of Oxford, Nuffield Department of Primary Care Health Sciences REVIEW RETURNED 26-Jul-2022

GENERAL COMMENTS
Myocardial Infarction and stroke subsequent to urinary tract infection (MISSOURI): protocol for a self-controlled case series using linked electronic health records To my mind this is an important question, with strong clinical relevance, and I suspect we are going to be glad to know the answer, if positive or negative. I agree this study design is an appropriate way to investigate the causal question, and I'm glad you did not shy away from using causal language.
First thoughts on objectives: why 90 days (I see this is mentioned in the Exposure section)? My simple minded approach to the mechanisms between infection and CVD are that 1. it might be accelerating atherosclerosis, or 2. it might be triggering existing disease (by increased cardiac output, type ii MI, pro-thrombotic states, etc etc), but with either of these I imagine the risk is likely highest in the early days. ? room for sensitivity analyses or multiple analyses as was done in the earlier RTI work? I suppose I'm saying I think it is interesting to know the period of risk as were we to be intervening in some way, this is going to be important information to know who is at risk and how long one should intervene for.
-Is ascertainment really a proxy for severity? -Organism is an interesting idea -What about antibiotics? Is there a natural experiment here?are people started on antibiotics who are then found to have a resistant organism at higher risk? I appreciate table 1it is very helpful.
Population -The agewhy start at 30? Pretty rare to have an MI or stroke in the 30s and are probably going to be due to slightly unusual causes, such as central venous thrombosis, trauma, subarachnoids, cancers, anomalous anatomy etc. As you are using first events I suspect a higher lower age bound would increase the relationship you are looking for, even though the numbers might be lower.
Outcomesany distinction between suptypes of stroke? (Though I appreciate this is horribly coded, in CPRD data at least -see Davidson for grim details). But to clarify, is this including TIA? Spinal strokes? Subdurals? (UTI, falls over, subdural is probably not the sequence of events that is of interest).
Exposure -See above -I think an analysis with different time periods would be interesting, shorter ones in particular.

Reviewer 1:
We thank the Reviewer for his comments. There are no issues for us to address.

Reviewer 2:
Comment: To my mind this is an important question, with strong clinical relevance, and I suspect we are going to be glad to know the answer, if positive or negative. I agree this study design is an appropriate way to investigate the causal question, and I'm glad you did not shy away from using causal language. Response: Thank you for the positive feedback about our study.
Comment: First thoughts on objectives: why 90 days (I see this is mentioned in the Exposure section)? My simple minded approach to the mechanisms between infection and CVD are that 1. it might be accelerating atherosclerosis, or 2. It might be triggering existing disease (by increased cardiac output, type ii MI, pro-thrombotic states, etc etc), but with either of these I imagine the risk is likely highest in the early days. ? room for sensitivity analyses or multiple analyses as was done in the earlier RTI work? I suppose I'm saying I think it is interesting to know the period of risk as were we to be intervening in some way, this is going to be important information to know who is at risk and how long one should intervene for. Response: We agree with the Reviewer that time period of greatest risk is important to determine. This is why we will estimate Incidence rate ratios (IRR) for 1-7, 8-14, 15-28 and 29-90 days after UTI for both MI and stroke (as stated in section 2.7 Statistical Analysis, page 10). If we find an effect of UTI, we hypothesise that the risk will be highest in the early days as you suggest, then decline with time. This would be reflected in higher IRRs for the earliest periods, and lower IRRs for the later periods.
Comment: Is ascertainment really a proxy for severity? Response: The different definitions of UTI in the primary and secondary analyses provide ascertainment in different clinical scenarios. These clinical scenarios are a proxy for severity: a clinician not requesting a urine sample would usually indicate milder cases. A clinician requesting a urine sample would often indicate greater severity of symptoms or that a treatment has failed. UTIs diagnosed in hospital would usually be more severe cases.

Comment:
Organism is an interesting idea Response: We agreewe plan to do sub-group analyses to assess the impact of different organisms. We have clarified this in the Sensitivity and sub-group analyses section on page 11. Comment: What about antibiotics? Is there a natural experiment here?are people started on antibiotics who are then found to have a resistant organism at higher risk? Response: This is an interesting question. We will conduct a sensitivity analysis restricting the definition of UTI to include only antibiotic prescriptions for nitrofurantoin (currently recommended 1st line therapy) to explore the effect of the choice of antibiotic, as stated in section 2.8, Sensitivity and sub-group analyses, page 11. As stated above, we will also examine the impact of different organisms. We are not examining the effect of resistant organisms as this is outside the scope of the main study, but we may include this as a sub-study if time and budget allows.
Comment: Population -The agewhy start at 30? Pretty rare to have an MI or stroke in the 30s and are probably going to be due to slightly unusual causes, such as central venous thrombosis, trauma, subarachnoids, cancers, anomalous anatomy etc. As you are using first events I suspect a higher lower age bound would increase the relationship you are looking for, even though the numbers might be lower. Response: We chose a lower age bound of 30 years to reduce the chance of including MIs and strokes due to congenital or other non-artherosclerotic causes. A lower age bound of 40 might reduce this chance further but would increase the chance of missing relevant events, especially given the greater burden of cardiovascular disease in Wales compared to the UK as a whole. Wales has higher years of life lost and disability-adjusted life-years than England [https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(18)32207-4/fulltext] , suggesting a lower age of onset of cardiovascular disease.

Comment:
Outcomesany distinction between suptypes of stroke? (Though I appreciate this is horribly coded, in CPRD data at least -see Davidson for grim details). But to clarify, is this including TIA? Spinal strokes? Subdurals? (UTI, falls over, subdural is probably not the sequence of events that is of interest). Response: We are not planning to distinguish between different subtypes of strokes due to the coding issues alluded to by the Reviewer. TIAs will be included in a sensitivity analyses that uses a wider definition of MI and stroke. This is described in section 2.8 Sensitivity and sub-group analyses, page 11. We are not including subdural haemorrhage or extradural haemorrhage for exactly the reason the reviewer suggests.
Comment: Exposure -See above -I think an analysis with different time periods would be interesting, shorter ones in particular. Response: See response above -incidence rate ratios (IRR) will be reported for 1-7, 8-14, 15-28 and 29-90 days.
Comment: Overallvery interesting study. Response: We thank the reviewer for their kind comments.